additional edits/cleanup and total book compile

BayesBasics.bib

@@ -11,12 +11,20 @@ @book{kruschke_doing_2010
 	keywords = {Mathematics / Applied, Mathematics / General}
 }
 
+@book{kruschke2014doing,
+  title={Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan},
+  author={Kruschke, John},
+  year={2014},
+  publisher={Academic Press}
+}
+
 @book{gelman_bda,
 	edition = {3rd},
 	title = {Bayesian Data Analysis},
 	isbn = {9781439840955},
 	abstract = {Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition   Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code   The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.},
 	language = {en},
+	url = {http://www.stat.columbia.edu/~gelman/book/},
 	author = {Gelman, Andrew and Carlin, John B. and Stern, Hal S. and Dunson, David B. and Vehtari, Aki and Rubin, Donald B.},
 	month = nov,
 	year = {2013},
@@ -137,16 +145,61 @@ @article{gelmanHwangVehtari
   publisher={Springer}
 }
 
-@article{gelmanVehtariWAIC,
-  title={WAIC and cross-validation in Stan},
-  author={Vehtari, Aki and Gelman, Andrew},
-  year={2014}
-}
+
 
 @book{mcelreath2016,
   title={Statistical Rethinking: A Bayesian Course with Examples in R and Stan},
   author={McElreath, Richard},
   volume={122},
   year={2016},
   publisher={CRC Press}
+}
+
+@book{mcelreath2020,
+  title={Statistical rethinking: A Bayesian course with examples in R and Stan},
+  author={McElreath, Richard},
+  year={2020},
+  publisher={Chapman and Hall/CRC}
+}
+
+@book{mcelreath2020statistical,
+  title={Statistical rethinking: A Bayesian course with examples in R and Stan},
+  author={McElreath, Richard},
+  year={2020},
+  publisher={Chapman and Hall/CRC}
+}
+
+
+@article{gelmanVehtariWAIC,
+  title={WAIC and cross-validation in Stan},
+  author={Vehtari, Aki and Gelman, Andrew},
+  year={2014}
+}
+
+@article{vehtari2017practical,
+  title={Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC},
+  author={Vehtari, Aki and Gelman, Andrew and Gabry, Jonah},
+  journal={Statistics and computing},
+  volume={27},
+  number={5},
+  pages={1413--1432},
+  year={2017},
+  publisher={Springer}
+}
+
+@article{vehtari2015pareto,
+  title={Pareto smoothed importance sampling},
+  author={Vehtari, Aki and Simpson, Daniel and Gelman, Andrew and Yao, Yuling and Gabry, Jonah},
+  journal={arXiv preprint arXiv:1507.02646},
+  year={2015}
+}
+
+@article{carpenter2017stan,
+  title={Stan: A probabilistic programming language},
+  author={Carpenter, Bob and Gelman, Andrew and Hoffman, Matthew D and Lee, Daniel and Goodrich, Ben and Betancourt, Michael and Brubaker, Marcus and Guo, Jiqiang and Li, Peter and Riddell, Allen},
+  journal={Journal of statistical software},
+  volume={76},
+  number={1},
+  year={2017},
+  publisher={Columbia Univ., New York, NY (United States); Harvard Univ., Cambridge, MA~…}
 }